A penalized likelihood approach for dealing with separation in count data regression model

Momenul Haque Mondol; M. Shafiqur Rahman; Wasimul Bari

doi:10.1080/03610918.2022.2057541

A penalized likelihood approach for dealing with separation in count data regression model

Momenul Haque Mondol
, M. Shafiqur Rahman
, Wasimul Bari

University of Barishal
University of Dhaka

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1799-1813
Number of pages	15
Journal	Communications in Statistics: Simulation and Computation
Volume	53
Issue number	4
DOIs	https://doi.org/10.1080/03610918.2022.2057541
State	Published - 2024
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus Subject Areas

Statistics and Probability
Modeling and Simulation

Keywords

Bias reduction
Jeffreys prior
Monotone likelihood
Score function
Zero-inflated Poisson model

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10.1080/03610918.2022.2057541

Cite this

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title = "A penalized likelihood approach for dealing with separation in count data regression model",

keywords = "Bias reduction, Jeffreys prior, Monotone likelihood, Score function, Zero-inflated Poisson model",

author = "Mondol, \{Momenul Haque\} and Rahman, \{M. Shafiqur\} and Wasimul Bari",

note = "Publisher Copyright: {\textcopyright} 2022 Taylor \& Francis Group, LLC.",

year = "2024",

doi = "10.1080/03610918.2022.2057541",

language = "English",

volume = "53",

pages = "1799--1813",

journal = "Communications in Statistics: Simulation and Computation",

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TY - JOUR

T1 - A penalized likelihood approach for dealing with separation in count data regression model

AU - Mondol, Momenul Haque

AU - Rahman, M. Shafiqur

AU - Bari, Wasimul

PY - 2024

Y1 - 2024

KW - Bias reduction

KW - Jeffreys prior

KW - Monotone likelihood

KW - Score function

KW - Zero-inflated Poisson model

UR - https://www.scopus.com/pages/publications/85128047105

UR - https://www.scopus.com/pages/publications/85128047105#tab=citedBy

U2 - 10.1080/03610918.2022.2057541

DO - 10.1080/03610918.2022.2057541

M3 - Article

AN - SCOPUS:85128047105

SN - 0361-0918

VL - 53

SP - 1799

EP - 1813

JO - Communications in Statistics: Simulation and Computation

JF - Communications in Statistics: Simulation and Computation

IS - 4

ER -

A penalized likelihood approach for dealing with separation in count data regression model

UN SDGs

ASJC Scopus Subject Areas

Keywords

Access to Document

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